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SPDL

SPDL (Scalable and Performant Data Loading) is a library and project to explore the design of performant data loading.

It provides flexible pipeline abstraction and a set of operations used for processing array data.

Documentation

Please checkout the documentation.

License

SPDL is BSD 2-Clause licensed, as found in the LICENSE file.

Citation

Please use the following BibTex for citing our project if you find it useful.

@misc{hira2025scalableperformantdataloading,
   title={Scalable and Performant Data Loading},
   author={Moto Hira and Christian Puhrsch and Valentin Andrei and Roman Malinovskyy and Gael Le Lan and Abhinandan Krishnan and Joseph Cummings and Miguel Martin and Gokul Gunasekaran and Yuta Inoue and Alex J Turner and Raghuraman Krishnamoorthi},
   year={2025},
   eprint={2504.20067},
   archivePrefix={arXiv},
   primaryClass={cs.DC},
   url={https://arxiv.org/abs/2504.20067},
}

Metadata

Release files for spdl-core 0.7.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for spdl-core 0.7.0
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spdl_core-0.7.0-py3-none-any.whl Python 3 none any Details

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